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Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome

Overview of attention for article published in Genetics Selection Evolution, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome
Published in
Genetics Selection Evolution, April 2018
DOI 10.1186/s12711-018-0391-0
Pubmed ID
Authors

Stephen J. Bush, Charity Muriuki, Mary E. B. McCulloch, Iseabail L. Farquhar, Emily L. Clark, David A. Hume

Abstract

mRNA-like long non-coding RNAs (lncRNAs) are a significant component of mammalian transcriptomes, although most are expressed only at low levels, with high tissue-specificity and/or at specific developmental stages. Thus, in many cases lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNAs, we compared de novo assembled lncRNAs derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNAs assembled in cattle and human. We then combined the novel lncRNAs with the sheep transcriptional atlas to identify co-regulated sets of protein-coding and non-coding loci. Few lncRNAs could be reproducibly assembled from a single dataset, even with deep sequencing of the same tissues from multiple animals. Furthermore, there was little sequence overlap between lncRNAs that were assembled from pooled RNA-seq data. We combined positional conservation (synteny) with cross-species mapping of candidate lncRNAs to identify a consensus set of ruminant lncRNAs and then used the RNA-seq data to demonstrate detectable and reproducible expression in each species. In sheep, 20 to 30% of lncRNAs were located close to protein-coding genes with which they are strongly co-expressed, which is consistent with the evolutionary origin of some ncRNAs in enhancer sequences. Nevertheless, most of the lncRNAs are not co-expressed with neighbouring protein-coding genes. Alongside substantially expanding the ruminant lncRNA repertoire, the outcomes of our analysis demonstrate that stochastic sampling can be partly overcome by combining RNA-seq datasets from related species. This has practical implications for the future discovery of lncRNAs in other species.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 20%
Student > Master 5 14%
Student > Doctoral Student 3 9%
Researcher 3 9%
Student > Postgraduate 3 9%
Other 6 17%
Unknown 8 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 29%
Agricultural and Biological Sciences 9 26%
Veterinary Science and Veterinary Medicine 3 9%
Chemical Engineering 1 3%
Sports and Recreations 1 3%
Other 1 3%
Unknown 10 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 October 2018.
All research outputs
#3,800,330
of 25,382,440 outputs
Outputs from Genetics Selection Evolution
#81
of 821 outputs
Outputs of similar age
#73,430
of 339,945 outputs
Outputs of similar age from Genetics Selection Evolution
#8
of 23 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 821 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,945 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.